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ConfusionFlow: A model-agnostic visualization for temporal analysis of classifier confusion [article]

Andreas Hinterreiter, Peter Ruch, Holger Stitz, Martin Ennemoser, Jürgen Bernard, Hendrik Strobelt, Marc Streit
2020 arXiv   pre-print
The confusion matrix is an established way for visualizing these class errors, but it was not designed with temporal or comparative analysis in mind.  ...  ConfusionFlow is model-agnostic and can be used to compare performances for different model types, model architectures, and/or training and test datasets.  ...  ACKNOWLEDGMENTS This work was supported in part by the State of Upper Austria (FFG 851460, Human-Interpretable Machine Learning) and the Austrian Science Fund (FWF P27975-NBL).  ... 
arXiv:1910.00969v3 fatcat:u4f2bl45z5b7fdelbls25su2cu